Flaw Detection Research Articles

The Peculiarities of Acoustic Normal Waves Propagation in Thin Porous Sheets of Thermally Expanded Graphite

Thermally expanded graphite belongs to a new class of graphite materials with unique physical, chemical and mechanical properties. Acoustic wave velocity is one of the most important characteristics for study of porous materials including thin porous sheets of thermally expanded graphite. In this paper peculiarities of symmetric mode S0 Lamb wave propagation and SH-wave with horizontal polarization in sheets of thermally expanded graphite are experimentally investigated. To determine their velocities a differential measurement scheme on the base of a low-frequency acoustic flaw detector DIO1000 LF and specialized piezoelectric transducers with dry point contact was used. Additionally the longitudinal wave velocity in direction of sheet thickness was determined using piezoelectric transducers based on polyvinylidene fluoride. Indicatrices of normal wave velocities in the rolling plane were plotted and it was shown that the maximum acoustic anisotropy is characteristic for the S0-mode. The velocity minimum corresponds to the longitudinal direction of the rolling plane in which the maximum elongation of gas pores was observed. Influence of thickness and density of thermally expanded graphite sheets on the velocities of normal waves was investigated and presence of the thickness range where the minimum velocity values were observed due to the maximum inhomogeneity of layers formed in the rolling process. Method for determination of dynamic elastic moduli of porous thermally expanded graphite sheets using experimentally measured velocities of normal waves was proposed. It was shown that in the longitudinal direction of the rolling plane the Poisson's ratio took negative values which allow to attribute the specified material to auxetics ones.

Fatigue Strength Analysis of Rail Fastening Baseplate

Superstructural elements of a railway track experience dynamic loads varying over time. As a consequence, this is accompanied by the initiation and accumulation of fatigue damages. Defects in intermediate rail fastening are quite difficult to identify using flaw detection methods, and some can be destructed. In particular, rail fastening baseplates often fail due to insufficient fatigue strength.Purpose: To investigate the fatigue strength of rail fastening baseplate.Methodology: Development of the mathematical model of deformation based on the finite element method (FEM). Strength analysis of the baseplate using the model of a variable-thickness slab resting on a nonlinear elastic foundation. The latter is modeled by a set of rods with nonlinear deformation and parameters determined by compression tests of the baseplate. A mathematical model developed in COSMOS software for the FE analysis of the stress-strain state of the baseplate at a time-varying load from rolling equipment and assembly forces from attaching the baseplate to the sleeper and rail.Research findings: The cyclic loading parameters are obtained at dangerous points of the baseplate and its durability is analyzed at different loads with respect to unevenness of track settlement and failure of bolt connections of rail fasteners. The influence of these factors on actual loads on the rail fastener is determined. It is found that the service life of the baseplate mainly depends on the dynamic load.

Flaw detection of railway catenary insulator based on DP-YOLOv5 algorithm with bright and dark channel enhancement

Abstract In order to ensure the timely detection of safety hazards in overhead transmission lines with railroad conductors and improve the accuracy of night insulator defect detection, this paper proposes the DP-YOLOv5 algorithm with dark and light channel enhancement optimization. It improves the night insulator image quality by introducing the dark and light channel enhancement algorithm, builds a lightweight network by combining the DP-BS module, and adds the Shuffle Attention module to enhance the feature extraction and ensure detection accuracy. At the same time, the EC-Loss loss function is used to optimize the prediction frame adjustment, accelerate the model convergence, and improve detection efficiency and accuracy. The simulation results show that the accuracy of DP-YOLOv5 is 95.3%, the recall is 94.8%, the average accuracy is 95.5%, and the FLOPs are 219.3. Compared with YOLOv5, the mapped value is improved by 0.9%, the F1 is improved by 1%, and the model parameter and FLOPs are reduced by 48.8% and 50.8%, respectively.

Optimization of Laser Cladding Process Parameters and Analysis of Organizational Properties of Mixer Liners

Aiming to address the wear and replacement inconvenience of concrete mixer liners, this study utilizes a laser cladding system to clad Fe60 alloy powder on the liner. It investigates the influence of different process parameters on the forming quality of the Fe60 alloy powder cladding layer. The optimal process parameters were obtained by weighted comprehensive evaluation, and single-layer multi-pass cladding experiments were carried out under the optimal process parameters to investigate the effects of a 30%, 40%, and 50% lap rate on the surface flatness and forming quality of the cladding layer. Using a metallographic microscope, a scanning electron microscope analysis of the macro morphology and microstructure of the cladding layer was conducted, a DPT-5 penetration flaw detector was used to observe the cracks on the surface of the multi-channel cladding, a microhardness tester and friction and wear experimental machine were used for the hardness of the cladding layer, and an abrasive wear resistance test was conducted. The results show that under the process parameters of a laser power of 900 W, powder feeding speed of 7 g/min, scanning speed of 600 mm/min, and 50% lap rate, the average microhardness of the fused cladding layer reaches 742 HV, which is 1.8 times higher than that of the liner plate, and the coefficient of friction is 0.57, which improves the liner plate’s wear resistance performance and service life.

Analysis of ultrasonic device influence on the ultrasonic thickness measurement of the steel grade

ABSTRACT Ultrasonic thickness measurement depends on the capability of the equipment and its operating characteristics, as well as on the auxiliary means used to adjust the system and analyse the obtained results. The characteristics of the ultrasonic device commonly used as a flaw detector are crucial for achieving accurate and precise results and are very important for the reliability of the results obtained in the measurement process, especially in production systems. This article aims to determine the quantitative variations in thickness caused by influencing parameters of the ultrasonic device and chosen ultrasonic probe, their quantification of interactions, and the significance of their influence on the accuracy and precision of the results. In the experimental part of the research, a factorial plan of the experiment was carried out to determine the influence of the ultrasonic device and the type of ultrasonic probe on the variability of the results of the ultrasonic thickness measurement. The parameters of the ultrasonic device and probes were analysed, and the experimental plan for developing the regression model was elaborated. The response surface methodology was applied, and the in-service measurement process was simulated using Monte Carlo simulation.

Imaging of microcrack propagation in 3D nanostructures applying laboratory nano-XCT

Abstract Laboratory X-ray microscopy and nano X-ray computed tomography (nano-XCT) have the unique capability to combine sub-100nm resolution and high object penetration. Therefore, these are appropriate non-destructive inspection techniques for the detection of flaws with a size of 100 nm and below in opaque objects and bulk materials. Another advantage of X-ray microscopy – as opposed to destructive failure analysis methods – is that kinetic processes such as microcrack evolution can be imaged. The unique combination of micromechanics and high-resolution 3D imaging allows to study degradation and failure mechanisms in opaque 3D nanopatterned structures, and it allows to provide essential information for fracture mechanics in small dimensions. The high-resolution in-situ/operando imaging of microcrack propagation in microelectronic products and in battery electrodes is demonstrated.

A novel enhancing method for terahertz imaging of integrated circuits flaw detection

This research paper addresses the current gap in understanding the intricate damage types within packaged integrated circuits (ICs). We introduce a novel and multiscale latent low-rank representation (M-LatLRR) methodology, meticulously tailored to enhance the quality of terahertz (THz) IC images and reveal latent features. By integrating THz imaging with our proposed M-LatLRR method, we aim to facilitate the precise identification of damage types within inside the packaged ICs. Firstly, the multiscale Gaussian functions are used to remove the blur and the components are obtained via averaging. Secondly, the image matrices are utilized to extract base matrices and detail matrices. With LatLRR, the multiscale detail matrices are extracted at several representation levels. The final enhanced image is reconstructed by average strategy for dealing with the detail and pre-enhancement parts. The M-LatLRR framework is universal and can be effectively applied to extract multi-level features of packaged IC images. In a comparative analysis, our method demonstrates superior capabilities in determining the failure types of fractured wire bonds, cracks, and delamination of the dielectric layer, outperforming alternative methodologies.

Research Progress on Novel Inspection of Oil and Gas Pipeline Integrity

Oil and gas pipeline integrity is the key to ensure the safety of energy transportation, with the development of science and technology, the research and application of new detection technology has been increasingly emphasized. This paper firstly describes the background and practical significance of the selected topic, aiming at exploring more efficient pipeline inspection methods to ensure the stable operation of energy networks. In terms of theoretical framework, we have sorted out the theoretical system of integrity management, including the core elements of risk assessment, inspection technology, and maintenance strategy, which provides a theoretical basis for the subsequent research. Then, we systematically review the latest progress of oil and gas pipeline integrity testing at home and abroad. From the dimensions of physical principle and application practice, we analyze the advantages and disadvantages of conventional ultrasonic and magnetic particle flaw detection, as well as the emerging acoustic emission and fiber grating inspection technologies, and show the application cases of each technology in actual projects. Through comparative analysis, we find that although conventional technologies meet the inspection needs to a certain extent, new inspection technologies such as remote monitoring based on the Internet of Things (IoT) and artificial intelligence-assisted diagnosis are gradually becoming a research hotspot due to their high precision, high efficiency and intelligent features. The development of these technologies not only improves the comprehensiveness and accuracy of inspection, but also provides strong support for realizing the whole life cycle management of pipelines. In the summary review section, we emphasize the future development trend of oil and gas pipeline integrity inspection, including the integration and intelligence of technology, as well as the deep mining and application of data. At the same time, we also point out the challenges in the current research, such as the unification of inspection standards and the establishment of data sharing mechanisms, which require the joint efforts of the research community and the industry to achieve the continuous improvement of oil and gas pipeline safety. To summarize, this paper aims to comprehensively show the research progress of new detection technology of oil and gas pipeline integrity, provide reference for researchers and engineering practitioners in related fields, and promote the further improvement of China's oil and gas pipeline safety management level.

Ultrasonic Lamb wave detection using a fiber-optic quasi-distributed acoustic sensing system.

The Lamb wave represents one of the most utilized forms of ultrasonic guided waves for flaw detection. A novel approach, to the best of our knowledge, for Lamb wave sensing using a fiber-optic quasi-distributed acoustic sensing (QDAS) system is proposed. Sensing elements constructed with optical weak reflectors are designed and analyzed, demonstrating the theoretical feasibility of establishing an ultrasonic sensing array comprising over 300 points. An empirical mode decomposition method is applied to this system to remove harmonic components in a frequency division multiplexed interrogation system. Verification experiments are carefully designed, employing compact 2.5 cm-sized sensing elements to capture 1 MHz Lamb wave signals on an aluminum plate. These findings significantly broaden the applicability of QDAS in the field of ultrasonic flaw detection.

Waveguide Acoustic Control of Pipes - Billets of Deep Rod Pumps

Deep rod pumps are expensive maintenance-free equipment for extracting oil from wells. The exclusion of defective billet pipes from the technological cycle of manufacturing elements of such pumps significantly affects both the cost of their production and the cost of production. A waveguide method is proposed for continuous input testing of tube billets of rod pump cylinders. It does not require scanning and is highly sensitive to both internal and surface defects. An experimental assessment of the sensitivity of the method to defects in the form of an influx located on the outer and inner surfaces of a thick-walled pipe with a diameter of 59.3 mm and a wall thickness of 14 mm was carried out. The echo signal from the artificial reflector decreased by 2 dB when the reflector was moved from the outside of the pipe to the inside. The criteria for rejection of the blank pipe are determined by the signal level at the first reflection R1, at the 8th reflection RN and by the attenuation coefficient b. As a result of flaw detection of billet pipes, a pipe with a significant defect was found. An experimental study of the acoustic properties of a batch of pipes with a diameter of 58 mm in the delivery state was carried out. For the billets of the cylinder of the deep rod pump in the delivery state, the lower acceptance limit for the torsional wave velocity of 3255 m/s has been determined. The influence of technological operations of high tempering and straightening on their acoustic properties is estimated. The possibility of quality control when performing the release operation by the guided wave method is shown. It was revealed that during the tempering procedure, the velocity of the torsional wave increases, on average, by 27 m/s per batch.

Model of occupational exposure of workers performing inspection of welded joints

A model of occupational exposure to gamma flaw detector operators working with portable flaw detectors in the field has been developed. The initial data for the development and verification of the model were the results of measurements of the characteristics of the gamma radiation field at the workplaces of flaw detectors and data from individual dosimetric monitoring. The relationships between the measured (H*(10), Hp(10)) and protection (effective dose) quantities (conversion coefficients) were determined using calculations and phantom experiments simulating three main operations of the full production cycle: transportation of the flaw detector to the place of X-raying of the product, installation of a flaw detector to perform x-raying and X-raying of the product. As a result of the study, it was found that more than 90% of the dose contribution to the readings of an individual dosimeter is due to the installation of the flaw detector in the working position and X-raying of the product. The values of the conversion coefficients for these operations in the form of the ratio of the effective dose values and the readings of dosimeters (Hp(10)) located on the worker's body at chest level (standard place) and abdominal level differ little for both positions of individual dosimeters. The use of maximum conversion coefficient value of 0.8 Sv/Sv corresponding to the operation of X-raying of the product will ensure conservatism in the assessment of the effective dose for the entire production cycle by no more than 15% and 25% for dosimeters located at the chest level and abdominal level, respectively.

An Experimental Assessment Using Acoustic Emission Sensors to Effectively Detect Surface Deterioration on Steel Plates

Acoustic emission (AE) testing is used for the continuous evaluation of structural integrity and the monitoring of damage evolution in structural components and materials. During operation, the environmental and loading conditions of metal structures can result in corrosion and surface wear damage. The early detection of surface degradation flaws is crucial, as they can serve as local stress concentration points, leading to crack initiation and failure. In this work, the effectiveness of AE in monitoring corrosion and surface wear flaw formation was experimentally evaluated. AE sensors were installed on steel test plates during the artificial induction of corrosion and surface wear in order to detect and record the generated AE signals. Corrosion-related AE signals typically exhibit low amplitude, count, and energy values. The direct detection of active corrosion can be challenging in noisy environments, but it can be carried out under certain conditions using dedicated AE sensor groups. Surface-wear-related AE signals exhibit high amplitude, energy, and count values, with long duration values that are associated with wear and grinding conditions. It was found that AE sensors can be utilised to detect corrosion and surface degradation events. The effectiveness of the AE method in detecting surface degradation in noisy environments can be improved by implementing a filtering methodology. This will limit the recording of noise-related signals that can mask out actual surface degradation AE events.

Developing flaw sizing methodology in Total Focusing Method (TFM) by EDM calibration blocks

The Total Focusing Method (TFM) represents a significant advancement in ultrasonic inspection, delivering high-resolution imaging by leveraging phased array technology combined with sophisticated data processing algorithms. This synergy enables detailed visualization of flaws in various materials, thereby improving flaw detection and characterization. Despite TFM's capabilities, the lack of a standardized methodology for flaw sizing limits its potential for flaw evaluation. This paper seeks to establish a new paradigm in flaw sizing by introducing a custom methodology specifically designed for TFM, using electrical discharge machined (EDM) calibration blocks that reflect a range of flaw shapes. The research highlights the limitations of conventional side-drilled holes (SDH) for capturing realistic flaw nuances and emphasizes the superior ability of EDM notches to simulate the complex geometries inherent in typical flaws. By investigating the influence of different TFM modes, the study provides insight into their effectiveness in improving the accuracy of flaw characterization. Our approach addresses the challenges of existing TFM practices, with EDM notches serving as an essential tool in methodological advancement. This work contributes to the continued development of best practices in TFM application, paving the way for more accurate, reliable, and versatile nondestructive testing.

Selected applications of satellite technologies in rail transport

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity requirements, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative documents. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the authors, the described methods can also be used in many other tasks related to rail transport.

Research of EDDY current probes for inspection of aluminum alloy structure welds using smartphone-based flaw detector

Research of EDDY current probes for inspection of aluminum alloy structure welds using smartphone-based flaw detector

Effectiveness of the technology of automated EDDY flaw detection with matrix converters

Effectiveness of the technology of automated EDDY flaw detection with matrix converters

Research on ultrasonic guided wave-based high-speed turnout switch rail base flaw detection

Turnout switch rail fracture detection is currently a serious issue in the field of railway transportation. Guided wave detection, a non-destructive testing method, is a good way of studying this issue and looking for a suitable solution. For this paper, a guided wave mode and an excitation position were selected based on the phase velocity dispersion curve and the wave structure. After this, a model was devised for the turnout switch area using the finite element (FE) method. This model considered the straight switch rail, curved stock rail, bolt hole, spacer block, and sub-rail foundation, and verifies the validity of the simulation model through the experiment. The propagation characteristics of guided waves in the switch rail were then simulated in different fracturing states by means of a 30-kHz excitation applied vertically to the rail base. The results showed that a single mode of the guided wave could be generated by this excitation method, showing that it could be used as an effective means for fracture detection. The growth rate of the root-mean-square (RMS) value of the time-domain acceleration signal could then be analysed to identify the state of fracture in the straight switch rail. This discrimination method is suitable for finding fractures parallel to the rail cross-section with a width of 5 mm or more at the bottom of the straight switch rail.

Quantitative Detection of Local Flaw Under the Lift-Off Effect for Steel Wire Ropes

Quantitative Detection of Local Flaw Under the Lift-Off Effect for Steel Wire Ropes

MAPOD analysis in eddy current testing of flaws considering multiple response signals and multiple flaw parameters

The reliability of the eddy current testing (ECT) in flaw detection is quantitatively evaluated by the probability of detection (POD). Precise and efficient modelling of POD gives direction for the implement of ECT on sites to avoid false or missing flaw detection. Traditional POD analysis focuses on single uncertain factor or single response signal with limited credibility in engineering. This paper considers multiple response signals and multiple flaw parameters to perform POD. The flaw length, the flaw depth, the coil impedance and the magnetic flux density are comprehensively studied under various lift-off distances. A finite element model (FEM) of ECT is established and verified with experiments to obtain sufficient simulation data for discrete POD modelling. The continuous POD function is then fitted based on the discrete values to show the superiority of integrating multiple factors. A comparison with conventional POD analysis further demonstrates the higher reliability of ECT flaw detection considering multiple flaw parameters and multiple response signals, especially for small flaws. Conflict of Interest Statement The authors declare no conflicts of interest.

Flaw Detection by SHM with Static Sensors Approach: State of the Art and Perspectives

AbstractStructural health monitoring (SHM) is a technology aimed to monitor the soundness of the structures. Applications for aircraft structures are largely investigated. The goal is to utilize the information acquired during the monitoring to save maintenance costs, improve flight safety, and design lighter structures. Different issues, like load monitoring and impact detection, are investigated by SHM research. The most largely investigated issue is damage detection, i.e., developing a system that utilizes sensors to detect the damage in the structure. Damage detection can be performed with two sensors: dynamic and static. Dynamic sensors work by transmission of waves through the structures. Defects are identified by deviation and reflection of the waves by damages. The SHM approach described in this work is based on static sensors, like strain gages or fiber optics. The strain fields under load in pristine and damaged conditions are compared; the evaluation of the change in the strain field identifies damages. Two different algorithms for damage detection have been developed and patented in Leonardo Aircraft and are described in this work; they are based on the reverse finite element model (FEM) and neural network. The issues related to the strain field measurement are also briefly described.